Dual Role of CXCL8 in Maintaining the Mesenchymal State of Glioblastoma Stem Cells and M2-Like Tumor-Associated Macrophages
Bibliographic record
Abstract
PURPOSE: The dynamic interplay between glioblastoma stem cells (GSC) and tumor-associated macrophages (TAM) sculpts the tumor immune microenvironment (TIME) and promotes malignant progression of glioblastoma (GBM). However, the mechanisms underlying this interaction are still incompletely understood. Here, we investigate the role of CXCL8 in the maintenance of the mesenchymal state of GSC populations and reprogramming the TIME to an immunosuppressive state. EXPERIMENTAL DESIGN: We performed an integrative multi-omics analyses of RNA sequencing, GBM mRNA expression datasets, immune signatures, and epigenetic profiling to define the specific genes expressed in the mesenchymal GSC subsets. We then used patient-derived GSCs and a xenograft murine model to investigate the mechanisms of tumor-intrinsic and extrinsic factor to maintain the mesenchymal state of GSCs and induce TAM polarization. RESULTS: We identified that CXCL8 was preferentially expressed and secreted by mesenchymal GSCs and activated PI3K/AKT and NF-κB signaling to maintain GSC proliferation, survival, and self-renewal through a cell-intrinsic mechanism. CXCL8 induced signaling through a CXCR2-JAK2/STAT3 axis in TAMs, which supported an M2-like TAM phenotype through a paracrine, cell-extrinsic pathway. Genetic- and small molecule-based inhibition of these dual complementary signaling cascades in GSCs and TAMs suppressed GBM tumor growth and prolonged survival of orthotopic xenograft-bearing mice. CONCLUSIONS: CXCL8 plays critical roles in maintaining the mesenchymal state of GSCs and M2-like TAM polarization in GBM, highlighting an interplay between cell-autonomous and cell-extrinsic mechanisms. Targeting CXCL8 and its downstream effectors may effectively improve GBM treatment.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".